The Application Of Data Mining For Larger Retail Bookstore

The larger retail bookstore has accumulated massive data after many years' informatization movement. How to analyze these data has already become the urgent matters needed to be solved by the enterprise. The statistical method characterized by gathering simply and analyzing according to the designated pattern, can not finish the analysis of this kind of data. Therefore, the application of data mining technology (including OLAP) becomes the inevitable choice.Although every year, a lot of papers and articles about data mining technology come out, there is exception to the book trade. This article first introduces the current information management systems of some larger retail bookstores. Then on the basis of the information management system, in view of the characteristic of book trade, put forward a realization frame of data mining system suitable for the larger retail bookstores. Further, based on this frame, introduce one kind of application base upon frequent-pattern growth algorithm, as well as one way of time-series data trend analysis. The preceding application may help put the books in the right place. While the latter method might help the enterprise to forecast the future sales tendency, so as to formulate the reasonable development plan.